Volume : 4, Issue : 4, APR 2020


Thamarai Kannan L, Gnana Baskaran A


The performance of mobile ad hoc network transmissions subject to disruption, loss, interference, and jamming can be significantly improved with the use of network coding (NC). Focusing on the Optimized Link State Routing (OLSR) protocol, an BM (Bandwdith Management) mechanism to accurately detect and isolate misbehavior node(s) in OLSR protocol based on End-to-End (E2E) communication between the source and the destination is proposed. The collaboration of a group of neighbor nodes is used to make accurate decisions.

Releasing social network data could seriously breach user privacy. User profile and friendship relations are inherently private. Unfortunately, sensitive information may be predicted out of released data through data mining techniques. Therefore, sanitizing network data prior to release is necessary. In this paper, we explore how to launch an Cheating Bandwidth attack exploiting social networks with a mixture of non-sensitive attributes and social relationships. We map this issue to a collective classification problem and propose a collective Cheating Bandwidth model. In our model, an attacker utilizes user profile and social relationships in a collective manner to predict sensitive information of related victims in a released social network dataset. To protect against such attacks, we propose a data sanitization method collectively manipulating user profile and friendship relations. Besides sanitizing friendship relations, the proposed method can take advantages of various data-manipulating methods. We show that we can easily reduce adversary's prediction accuracy on sensitive information, while resulting in less accuracy decrease on non-sensitive information towards three social network datasets. This is the first work to employ collective methods involving various data-manipulating methods and social relationships to protect against Cheating Bandwidth attacks in social networks.


Article : Download PDF

Cite This Article

Article No : 6

Number of Downloads : 1


  1. -H. Lee, M. Gerla, H. Krawczyk, K.-W. Lee, and E. A. Quaglia, “Quantitative evaluation of secure network coding using homomorphic signature/hashing,” in Proc. NetCod, Beijing, China, Jul. 2011, pp. 1–10.
  2. Joy, Y. Yu-Ting, V. Perez, D. Lu, and M. Gerla, “A new approach to coding in content-based MC-Computings,” in Proc. Int. Conf. Comput., Netw. Commun. (ICNC), Honolulu, HI, USA, Feb. 2014, pp. 173–177.
  3. Buttyán, L. Dóra, M. Félegyházi, and I. Vajda, “Barter trade improves message delivery in opportunistic networks,” Ad Hoc Netw., vol. 8, no. 1, pp. 1–14, Jan. 2010.
  4. Zhang and M. van der Schaar, “Peer-to-peer multimedia sharing based on social norms,” Image Commun., vol. 27, no. 5, pp. 383–400, May 2012.
  5. Chen, F. Wu, and S. Zhong, “FITS: A finite-time Cheating Bandwidth system for cooperation in wireless ad hoc networks,” IEEE Trans. Comput., vol. 60, no. 7, pp. 1045–1056, Jul. 2010.
  6. Chen and S. Zhong, “INPAC: An enforceable incentive scheme for wireless networks using network coding,” in Proc. IEEE INFOCOM, Mar. 2010, pp. 1828–1836.
  7. Wu, M. Gerla, and M. van der Schaar, “Social norm incentives for secure network coding in MC-Computings,” in Proc. IEEE NetCod, Jun. 2012, pp. 179–184.
  8. Dong, R. Curtmola, and C. Nita-Rotaru, “Practical defenses against pollution attacks in wireless network coding,” ACM Trans. Syst. Inf. Secur., vol. 14, no. 1, May 2011, Art. no. 7.
  9. Yang, Y. L. Sun, S. Kay, and Q. Yang, “Defending online Cheating Bandwidth systems against collaborative unfair raters through signal modeling and trust,” in Proc. 24th ACM Symp. Appl. Comput., Mar. 2009, pp. 1308–1315.
  10. Yu, Y. Wei, B. Ramkumar, and Y. Guan, “An efficient signature-based scheme for securing network coding against pollution attacks,” in Proc. IEEE INFOCOM, Apr. 2008, pp. 1409–1417.
  11. Price and T. Javidi, “Network coding games with unicast flows,” IEEE J. Sel. Areas Commun., vol. 26, no. 7, pp. 1302–1316, Sep. 2008.
  12. Zhang and B. Li, “Dice: A game theoretic framework for wireless multipath network coding,” in Proc. MobiHoc, 2008, pp. 293–302.
  13. R. Marden and M. Effros, “The price of selfishness in network coding,” in Proc. 5th Workshop Netw. Coding Theory Appl., Jun. 2009, pp. 18–23.
  14. Zhu and H. Shen, “TrustCode: P2P Cheating Bandwidth-based trust management using network coding,” in Proc. 15th Int. Conf. High Perform. Comput., Bangalore, India, Dec. 2008.
  15. Shevade, H. H. Song, L. Qiu, and Y. Zhang, “Incentive-aware routing in DTNs,” in Proc. IEEE ICNP, Orlando, FL, USA, Oct. 2008, pp. 238–247.